Undesirable factors in stochastic cross-efficiency evaluation

Cross-efficiency evaluation in Data envelopment analysis (DEA) has been accepted as a useful tool for performance evaluation and ranking of decision making units. In this paper using Undesirable Multiple Form (UMF) model with specific risk of α, a new stochastic model called Expected Ranking Criterion is introduced using statistical techniques for efficiency evaluation decision making units (DMU). Another issue in applying cross-efficiency DEA models is considering stochastic in input and output variables. Also, the non-uniqueness of optimal weights in this evaluation has reduced the usefulness of this powerful method. As a result, it is recommended that secondary goals be introduced in cross-efficiency evaluation. In this paper, the cross-efficiency model is modified to deal with stochastic data by applying chance-constrained approach.